Visible-light-image physiological monitoring system with thermal detecting assistance

ABSTRACT

A visible-light-image physiological monitoring system with thermal detecting assistance is disclosed. The system takes a visible-light image and a thermal image of a body at the same time. A processing unit identifies a body feature of the visible-light image and determines a coordinate of the feature. In a learning mode, an initial temperature of the body feature is determined from the thermal image according to the coordinate of the body feature. After then, a physiological status monitoring mode is executed to monitor the temperature changes of the body feature and output an alarm when the temperature is determined to be abnormal. Therefore, a monitoring accuracy of the visible-light-image physiological monitoring system is increased and avoids transmitting false alarms or no alarms.

CROSS-REFERENCE TO RELATED APPLICATIONS

This application is based upon and claims priority under 35 U.S.C. 119from Taiwan Patent Application No. 109116098 filed on May 14, 2020,which is hereby specifically incorporated herein by this referencethereto.

BACKGROUND OF THE INVENTION 1. Field of the Invention

The present invention is related to a visible-light-image physiologicalmonitoring system, and more particularly to a visible-light-imagephysiological monitoring system with thermal detecting assistance.

2. Description of the Prior Arts

At present, many image monitoring devices or systems have come out toprovide remote user real images at local. With the advancement of imageprocessing technology, the image monitoring devices or systems canidentify any human body shown in the images and further analyzes thehuman body's motion. Therefore, the remote user does not necessarilymonitor the images from the image monitoring devices or systems to watchpeople's activities at local.

In a baby monitoring application, a baby monitor is placed in baby'sroom and an alarm device linking the baby monitor is portable forparents. The parents can watch the baby through the alarm device. Thealarm device further has an alarming function with identification meansto help the parents determine whether the baby on the bed may be indanger and quickly remove the danger matter. For example, when the quiltcovers the baby's mouth and nose to cause difficulty breathing of thebaby, the alarm device analyzes the baby's photo-images from the babymonitor to determine that the quilt covers the baby's mouth and nose.However, in different situations, such as vomiting milk or having afever, the alarm device can not determine these dangerous situations forthe baby by analyzing the baby's photo-images. Therefore, when theparents rely on the baby monitor excessively and the baby monitor cannot determine most dangerous situations caused the baby's death, it is ahigh risk for baby care by using the conventional baby monitor.

To overcome the shortcomings, the present invention provides avisible-light-image physiological monitoring system with thermaldetecting assistance to mitigate or to obviate the aforementionedproblems.

SUMMARY OF THE INVENTION

An objective of the present invention is to provide avisible-light-image physiological monitoring system with thermaldetecting assistance.

To achieve the objective as mentioned above, the visible-light-imagephysiological monitoring system with thermal detecting assistance has:

a casing;

a visible-light image sensor mounted on the casing and outputtingmultiple visible-light images of a body;

a thermal sensor movably mounted on the casing and outputting multiplethermal images, wherein a resolution of the thermal image is less thanthat of the visible-light image;

a first communication module mounted in the casing; and

a processing unit mounted in the casing and electrically connected tothe visible-light image sensor and the thermal sensor to receive thevisible-light images and the thermal images, and controlling the thermalsensor to move relative to the casing, wherein the processing unitidentifies multiple features of the body from the visible-light imagesand determines multiple coordinates of the features through adeep-learning module; the processing unit is electrically connected tothe first communication module to transmit a physiological monitoringalarm through the first communication module; and the processing unithas a physiological status determining procedure having:

-   -   a learning mode generating an initial temperature of the at        least one feature of the body; and    -   a physiological status monitoring mode continuously receiving        the visible-light images, and continuously receiving the thermal        images of the at least one feature of the body from the thermal        sensor after the thermal sensor is controlled to move and to        correspond the at least one feature of the body; determining a        temperature of the at least one feature from the received        thermal images corresponding to the at least one feature        according to the initial temperature and the coordinate of the        least one feature; and transmitting the physiological monitoring        alarm when the temperature is determined to be an abnormal        temperature.

With the foregoing description, the visible-light-image physiologicalmonitoring system of the present invention receives the visible-lightimages of the body and the thermal images of the feature of the body atthe same time. The present invention uses the deep-learning module toaccurately identify the at least one feature of the body and thecoordinates thereof. Furthermore, the processing unit controls thethermal sensor to correspond a position of the feature of the bodyaccording to the corresponding feature to receive the thermal image ofthe feature. Therefore, the processing unit executed the learning modeto identify the features of the body and multiple coordinates of thefeatures and further obtains the body's initial temperature from thethermal image according to the at least one feature and the coordinatethereof. The physiological status monitoring mode is then executed tomonitor one of the feature's temperature changes. The physiologicalmonitoring alarm will be transmitted if the temperature is determined tobe abnormal. Therefore, the present invention can set a real normaltemperature of the body to be monitored as the initial temperature, andaccurately monitors the temperature variation of the body's specificfeature to reduce the chance of false alarms.

Other objectives, advantages and novel features of the invention willbecome more apparent from the following detailed description when takenin conjunction with the accompanying drawings.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 is a schematic view of a visible-light-image physiologicalmonitoring system mounted to a bedside in accordance with the presentinvention;

FIG. 2 is a perspective view of the visible-light-image physiologicalmonitoring system in accordance with the present invention;

FIG. 3 is a schematic view of one visible-light image;

FIG. 4A is a functional block diagram of a first embodiment of thevisible-light-image physiological monitoring system in accordance withthe present invention;

FIG. 4B is a functional block diagram of a second embodiment of thevisible-light-image physiological monitoring system in accordance withthe present invention;

FIGS. 5A and 5B are a partial visible-light image and a thermal imagecorresponding to the partial visible-light image in accordance with thepresent invention;

FIGS. 6A and 6B are another partial visible-light image and a thermalimage corresponding to the partial visible-light image in accordancewith the present invention;

FIGS. 7A and 7B are another partial visible-light image and a thermalimage corresponding to the partial visible-light image in accordancewith the present invention;

FIG. 8 is a pixel chart of an image area of FIG. 5B showing temperaturesthereof;

FIG. 9A is a flow chart of a learning mode in accordance with thepresent invention;

FIG. 9B is a flow chart of a physiological status monitoring mode inaccordance with the present invention; and

FIGS. 10A to 10D are temperature diagrams of four different monitoredstatuses in accordance with the present invention.

DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

With multiple embodiments and drawings thereof, the features of thepresent invention are described in detail as follows.

With reference to FIG. 1 , a visible-light-image physiologicalmonitoring system 1 of the present invention is a fixed system so thesystem may be mounted on a bedside 70 or around a bed to monitordifferent physiological states of a body 80 on the bed. With furtherreference to FIGS. 2 and 4A, the system 1 has a casing 10, avisible-light image sensor 20, a thermal sensor 30, a firstcommunication module 40, a processing unit 50 and an audio receiver 60.

In the preferred embodiment, at least one through hole 11 is formedthrough the casing 10 and a dual-shaft moving device 12 is mounted inthe casing. The audio receiver 60 receives an environmental audio fromthe through hole 11 and outputs an audio signal.

The visible-light image sensor 20 is mounted on the casing 10 andoutputs a visible-light image F1, as shown in FIG. 3 . The visible-lightimage sensor 20 aims to the bed and a shooting range of thevisible-light image sensor 20 covers a bed surface 71 of the bed. When abody in the bed, the visible-light image sensor 20 outputs thevisible-light image F1 of the body.

The thermal sensor 30 is movably mounted on the casing 10 and outputs athermal image F2, as shown in FIG. 5B. In the preferred embodiment, thethermal sensor 30 is a matrix thermal sensor 32 so the thermal image F2outputted from the thermal sensor 30 has multiple pixels. Each of thepixel contains a temperature value. In one embodiment, a resolution ofthe thermal image F2 is less than that of the visible-light image F3. Asshown in FIGS. 2 and 4A, since the thermal sensor 30 is mounted on thedual-shaft device 12, two motor modules 31 are further connected to thedual-shaft device 12 and electrically connected to the processing unit50. According to the coordinate of the feature, the processing unit 50drives the two motor modules 31 to move the dual-shaft device 12 and thematrix thermal sensor 32 relative to the casing 10. Therefore, thematrix thermal sensor 32 is moved to correspond one of feature of thebody according to the coordinate of the feature and then output thethermal image of the corresponding feature of the body. With furtherreference to FIG. 4B, a second embodiment of a visible-light-imagephysiological monitoring system 1 of the present invention is shown. Thevisible-light-image physiological monitoring system is similar to thatof FIG. 4A, but a thermal sensor 30′ is a single-point thermal sensor32′. The two motor modules 31 are electrically connected to theprocessing unit 50 and connected to the dual-shaft moving device 12 ofthe casing 10. The processing unit 50 drives the two motor modules 32 tomove the dual-shaft moving device 12 and the thermal sensor 30′ on thecasing 10. Therefore, the thermal sensor 30′ is moveable relative to thecasing 10, so a sensing direction of the thermal sensor 30′ isadjustable. In particular, the single-point thermal sensor 32′ aims andscans the feature of the body and then outputs the thermal image F2 ofthe at least one feature.

The first communication module 40 is mounted in the casing 10. In oneembodiment, the first communication module 40 matches a wirelesscommunication device 72, such as WIFI or Bluetooth, etc.

The processing unit 50 is mounted in the casing 10 and electricallyconnected to the visible-light image sensor 20, the thermal sensor 30and the audio receiver 60 to receive the visible-light image F1, thethermal image F2 and the audio signal. In one embodiment, the processingunit 50 may be an AI processor having a built-in deep-learning module51. The deep-learning module 51 identifies a plurality of the body'sfeatures from the visible-light image and further determines acoordinate of each feature. The processing unit 50 is electricallyconnected to the first communication module 40 and transmits aphysiological monitoring alarm to the wireless communication device 72through the first communication module 40. In one embodiment, thevisible-light-image physiological monitoring system further has a cloudserver 52. The processing unit 50 may link the cloud server 52 through asecond communication module 41. The processing unit 50 may upload thereceived visible-light images to the cloud server 52. The cloud server52 has a deep-learning module 51 to identify the plurality of featuresof the body from the received visible-light images and the features'coordinates. The cloud server 52 sends the processing unit 50 theidentified features and the determined coordinates thereof. Theprocessing unit 50 further has a physiological status determiningprocedure having a learning mode and a physiological status monitoringmode. The processing unit 50 further determines a decibel value of thereceived audio signal from the audio receiver 60.

The learning mode generates an initial temperature of at least onefeature of the body to be monitored, as shown in FIG. 9A. The learningmode has following steps of S10 to S17.

In the step S10, with reference to FIGS. 3 and 5B, the visible-lightimage F1 and the thermal image F2 of the body to be monitored areobtained from the visible-light image sensor 20 and the thermal sensor30 at the same time.

In the step S11, at least one feature of the body to be monitored isidentified from the visible-light image F1 and the coordinate of eachfeature is determined. In one embodiment, with reference to FIGS. 5A, 6Aand 7A, the at least one feature of the body to be monitored may includea first feature F11, a second feature F12 and a third feature F13. Thefirst feature F11 contains the area of the eyes and a vicinity thereof.The second feature F12 contains the area of the mouth and a vicinitythereof. The third feature F13 contains the area of a butt and avicinity thereof.

In the step S12, at least one of the image areas F21, F22 and F23 of thethermal image F2 corresponding to the visible-light image are extractedaccording to the coordinate of the at least one of the features F11, F12and F13. With reference to FIGS. 5A and 5B, the coordinates of the firstfeature F11 of the visible-light image F1 are determined by thedeep-learning module 51. The image area corresponding to the firstfeature is determined from the thermal image F2 according to the firstfeature F11. Each pixel of the image area has one temperature value.With reference FIGS. 6A and 6B, the second feature F12 of thevisible-light image F1 are determined by the deep-learning module 51.The image area F22 corresponding to the second feature F12 is determinedfrom the thermal image F2 according to the coordinates of the secondfeature F12. Each pixel of the image area F22 has one temperature value.With reference FIGS. 7A and 7B, the coordinates of the third feature F13of the visible-light image F1 are determined by the deep-learning module51. The image area F23 corresponding to the third feature F13 isdetermined from the thermal image F2 according to the coordinates of thethird feature F13. Each pixel of the image area F23 has one temperaturevalue.

In the step S13, the temperature values of the image areas F21, F22 andF23 are read. For example, as shown in FIG. 8 , the temperature valuesof all pixels of the image area F21 of FIG. 5B are shown.

In the step S14, a temperature of the at least one feature is determinedaccording to the temperature values of the image areas F21, F22 and F23.In one embodiment, a maximum of the temperature values of each imagearea F21, F22 or F23 is selected to be represented as the temperature ofthe corresponding feature. In one embodiment, the temperature values ofall pixels of each image areas F21, F22 or F23 are summed and averagedas the temperature of the corresponding feature in this step.

In the step S15, a temperature of the at least one feature is determinedwhether falls in a first tolerance range. If so, then in the step S16, acumulative amount is increased by one and the cumulative amount isdetermined whether reaches N. If the temperature of the at least onefeature is determined as not falling in the first tolerance range or thecumulative amount is determined as not reaching N, the steps S10 to S14are repeated. If the cumulative amount is determined as reaching N inthe step S16, the step S17 is then executed to determine one of thetemperatures falling in the first tolerance range as an initialtemperature of the corresponding feature of the body to be monitored onthe bed.

The physiological status monitoring mode is executed after the learningmode is finished. With reference to FIG. 9B, in the physiological statusmonitoring mode, multiple visible-light images and thermal images arecontinuously received. A physiological monitoring alarm may be generatedwhen the temperature of the at least one feature is determined asabnormal based on the initial temperature. The physiological statusmonitoring mode has following steps S20 to S28 and S211.

In the step S20, the visible-light image and the thermal image of thebody to be monitored are received from the visible-light image sensor 20and the thermal sensor 30.

In the step S21, the least one feature and the coordinate thereof aredetermined from the visible-light image. In one embodiment, as shown inFIGS. 5A, 6A and 7A, the least one feature may include one of the firstfeature F11, the second feature F12 and the third feature F13. Inaddition, if no feature of the body to be monitored is identified fromthe visible-light image in this step, go to the step S211.

In the step S22, at least one image area F21, F22 or F23 of the thermalimage F2 corresponding to the visible-light image are extractedaccording to the coordinate of the at least one feature F11, F12 or F13.With reference to FIGS. 5A, 5B, 6A, 6B, 7A and 7B, the coordinates ofthe first feature F11, the coordinates of the second feature F12 and thecoordinates of the third feature F13 of the visible-light image F1 aredetermined by the deep-learning module 51. The image areas F21, F22 andF23 corresponding to the above features F11, F12 and F13 are determinedfrom the thermal image F2 according to the coordinates of the featuresF11, F12 and F13. Each pixel of the image areas F21, F22 and F23 has onetemperature value.

In the step S23, the temperature values of the image areas F21, F22 andF23 are read. For example, as shown in FIG. 8 , the temperature valuesof all pixels of the image area F21 of FIG. 5B are shown.

In the step S24, a temperature of the at least one feature is determinedaccording to the temperature values of the image areas F21, F22 and F23.In one embodiment, a maximum of the temperature values of each imagearea F21, F22 or F23 is selected to be represented as the temperature ofthe corresponding feature. In one embodiment, the temperature values ofall pixels of each image area F21, F22 or F23 are summed and averaged asthe temperature of the corresponding feature in this step.

In the step S25, a temperature of the at least one feature is determinedwhether exceeds a first tolerance range of the initial temperature. Ifso, then in the step S26, a cumulative amount is increased by one andthe cumulative amount is determined whether reaches M. If thetemperature of the at least one feature is determined as exceeding thefirst tolerance range according to the initial temperature or thecumulative amount is determined as not reaching M, the steps S20 to 24are repeated. If the cumulative amount is determined as reaching M inthe step S26, the step S27 is then executed.

In the step S27, a temperature variation of the temperatures exceedingthe first tolerance range of the initial temperature is determined aswhether matches an abnormal temperature trend, i.e. a temperature riserate within a preset period. If matches, go to the step S28. In the stepS28, the processing unit 50 transmits the physiological monitoring alarmthrough the first communication module 40. If not matches, for example,as shown in FIG. 10B, the temperature variation is not going up, go tothe step S20. In a baby monitor application (the body to be monitored isa baby's body), as shown in FIGS. 10A and 5B, when the temperaturevariation is going up, the temperature variation is determined amatching the abnormal temperature trend. It means that the temperatureof one part of the baby's body is increased quickly. For example, asshown in FIG. 5B, if the temperature of the first feature is increasedquickly, the baby may have a fever and the processing unit 50 transmitsa fever alarm. For example, as shown in FIG. 7B, if the temperature ofthe third feature is increased quickly, the baby may pee or shit on thediaper, the processing unit 50 transmits a diaper alarm. With referenceto FIGS. 10C and 6B, if the temperature variation is going down andmatch another abnormal temperature trend, i.e. a temperature declinerate within a preset period. For example, as shown in FIG. 6B, if thetemperature of the second feature is decreased quickly, the baby mayvomit milk and the processing unit 50 transmits a milk-vomiting alarm.On the other hand, with reference to FIG. 10D, if the temperature of thesecond feature is not decreased quickly and the temperature variationdoes not match the abnormal temperature trend, the processing unit 50does not determine that the baby vomits milk and go to the step S20.

In addition, in the step S27, if the temperature variation matches theabnormal temperature trend (temperature rise rate within a presetperiod), the processing unit 50 further calculates the decibel value ofthe received audio signal from the audio receiver 60 and determineswhether the decibel value exceeds a preset decibel value. In the babymonitor application, the body to be monitored is the baby's body and thebaby may have a fever and is crying or coughing if the decibel valueexceeds the preset decibel value. The processing unit 50 transmits acoughing alarm or crying alarm.

In the step S211, the highest temperature value is extracted from thethermal image. The processing unit 50 determines whether the highesttemperature value is lower than a lowest temperature of a secondtolerance range of a normal body's temperature. If not, the processingunit 50 transmits the physiological monitoring alarm. In this situation,when the baby is on the bed and the temperature of the body is sensedbut not one of the features of the body is identified from thevisible-light image, the eyes or mouth of the baby may be covered bysomething or prone sleeping. The processing unit 50 transmits thephysiological monitoring alarm, such as a covered mouth alarm or a pronesleeping alarm. On the other hand, when the highest temperature value islower than the lowest temperature in a second tolerance range of anormal body temperature, the baby may be not on the bed and theprocessing unit 50 does not transmit the physiological monitoring alarm.

Based on the foregoing description, the visible-light-imagephysiological monitoring system of the present invention receives thevisible-light images of the body and the thermal images of the featureof the body at the same time. The present invention uses thedeep-learning module to accurately identify the at least one feature ofthe body and the coordinates thereof. Furthermore, the processing unitcontrols the thermal sensor to correspond a position of the feature ofthe body according to the corresponding feature to receive the thermalimage of the feature. Therefore, the processing unit executed thelearning mode to identify the features of the body and multiplecoordinates of the features and further obtains the body's initialtemperature from the thermal image according to the at least one featureand the coordinate thereof. The physiological status monitoring mode isthen executed to monitor one of the feature's temperature changes. Thephysiological monitoring alarm will be transmitted if the temperature isdetermined to be abnormal. Therefore, the present invention can set areal normal temperature of the body to be monitored as the initialtemperature, and accurately monitors the specific feature's temperaturevariation by analyzing the specific feature's thermal images, andfurther determines whether any abnormal temperature change occurs. Ifthe abnormal temperature variation occurs, the processing unitimmediately transmits the alarm. Furthermore, the processing unit alsoanalyzes the visible-light images to determine whether any dangerousbody action of the baby occurs, such as sleep on all fours, nose ormouth covered by close or quilt. Therefore, the temperature of thebaby's body captured by the thermal sensor increases the alarmingaccuracy of the processing unit in determining such dangerous actions.The processing unit avoids transmitting the false alarms or no alarm.

Even though numerous characteristics and advantages of the presentinvention have been set forth in the foregoing description, togetherwith the details of the structure and features of the invention, thedisclosure is illustrative only. Changes may be made in the details,especially in matters of shape, size, and arrangement of parts withinthe principles of the invention to the full extent indicated by thebroad general meaning of the terms in which the appended claims areexpressed.

What is claimed is:
 1. A visible-light-image physiological monitoringsystem with thermal detecting assistance, comprising: a casing; avisible-light image sensor mounted on the casing and outputting multiplevisible-light images of a body; a thermal sensor movably mounted on thecasing and outputting multiple thermal images, wherein a resolution ofthe thermal image is less than that of the visible-light image; a firstcommunication module mounted in the casing; and a processing unitmounted in the casing and electrically connected to the visible-lightimage sensor and the thermal sensor to receive the visible-light imagesand the thermal images, and controlling the thermal sensor to moverelative to the casing, wherein the processing unit identifies multiplefeatures of the body from the visible-light images and determinesmultiple coordinates of the features through a deep-learning module; theprocessing unit is electrically connected to the first communicationmodule to transmit a physiological monitoring alarm through the firstcommunication module; and the processing unit has a physiological statusdetermining procedure having: a learning mode generating an initialtemperature of the at least one feature of the body; and a physiologicalstatus monitoring mode having steps of: (b1) continuously receiving thevisible-light images; (b2) identifying at least one feature of thevisible-light image and determining a coordinate of each of the at leastone feature; (b3) controlling the thermal sensor to face a position ofthe least one feature of the body according to the coordinate of thecorresponding feature to continuously receive the thermal images of theat least one feature of the body from the thermal sensor; (b4)determining a current temperature of each of the at least one featurefrom the received thermal images; and (b5) transmitting thephysiological monitoring alarm when the current temperature isdetermined to be an abnormal temperature according to the initialtemperature.
 2. The visible-light-image physiological monitoring systemas claimed in claim 1, wherein the learning mode of the physiologicalstatus determining procedure has steps of: (a1) receiving thevisible-light image from the visible-light image sensor and the thermalimage from the thermal sensor at the same time; (a2) identifying atleast one feature of the visible-light image and determining acoordinate of each of the at least one feature; (a3) extracting an imagearea of the thermal image according to the coordinate of thecorresponding feature; (a4) reading a temperature value of each pixel ofthe image area; (a5) determining a temperature of the feature accordingto the temperature values of the corresponding image area; and (a6)determining whether the temperature of the feature falls in a firsttolerance temperature range, wherein if a determined result is positive,a cumulative amount is increased by one and the cumulative amount isdetermined whether reaches N, and if the determined result is negativeor the cumulative amount is determined as not reaching N, the steps (a1)to (a5) are repeated, wherein if the cumulative amount is determined asreaching N, one of the temperatures falling in the first tolerance rangeis the initial temperature.
 3. The visible-light-image physiologicalmonitoring system as claimed in claim 2, wherein in the step (a5), amaximum of the temperature values of the image area is selected to berepresented as the temperature of the corresponding feature; or in thestep (a5), the temperature values of the image area are summed andaveraged as the temperature of the corresponding feature.
 4. Thevisible-light-image physiological monitoring system as claimed in claim1, wherein the step (b4) of the physiological status monitoring modecomprises: (b41) extracting an image area of the thermal image accordingto the coordinate of the corresponding feature; (b42) reading atemperature values of each pixel of the image area; (b43) determining atemperature of the feature according to the temperature values of thecorresponding image area; and (b44) determining whether the temperatureexceeds the first tolerance range of the initial temperature; wherein ifa determining result is positive, a cumulative amount is increased byone and the cumulative amount is determined whether reaches M, and ifthe determined result is negative or the cumulative amount is determinedas not reaching M, the steps (b1) to (b5) and (b41) to (b43) arerepeated, wherein if the cumulative amount is determined as reaching M,go to a step (b45); and (b45) determining whether a temperaturevariation of the M temperatures matches a normal temperature trend;wherein, if a determining result is positive, the processing unittransmits the physiological monitoring alarm through the firstcommunication module, but if a determining result is negative, go to thestep (b1).
 5. The visible-light-image physiological monitoring system asclaimed in claim 4, wherein in the step (b45), the temperature variationof the M temperatures is a temperature rising trend, and the normaltemperature trend is an abnormal temperature rising trend.
 6. Thevisible-light-image physiological monitoring system as claimed in claim4, wherein in the step (b45), the temperature variation of the Mtemperatures is a temperature declining trend, and the normaltemperature trend is an abnormal temperature declining trend.
 7. Thevisible-light-image physiological monitoring system as claimed in claim1, wherein the casing further comprises: a dual-shaft moving device onwhich the thermal sensor is mounted; and two motor modules electricallyconnected to the processing unit and connected to the dual-shaft movingdevice, wherein the processing unit drives the motor modules to move thedual-shaft moving device along two axis directions.
 8. Thevisible-light-image physiological monitoring system as claimed in claim7, wherein the thermal sensor is a matrix thermal sensor or asignal-point thermal sensor.
 9. The visible-light-image physiologicalmonitoring system as claimed in claim 4, wherein in the step (b2), whenno one of the at least one feature of the visible-light image isidentified, go to a step of: (b6) extracting a highest temperature fromthe thermal image and determining whether the highest temperature islower than a lowest temperature in a second tolerance range of a normalbody temperature, wherein if a determining result is negative, thephysiological monitoring alarm is transmitted.
 10. Thevisible-light-image physiological monitoring system as claimed in claim9, wherein the least one feature is nose or mouth and the physiologicalmonitoring alarm is a covered mouth alarm or a prone sleeping alarm. 11.The visible-light-image physiological monitoring system as claimed inclaim 9, wherein the processing unit is further electrically connectedto an audio receiver to receive an audio signal and determine a decibelvalue of the audio signal.
 12. The visible-light-image physiologicalmonitoring system as claimed in claim 11, wherein in the step (b45), thedecibel value of the audio signal is obtained to further determinedwhether the decibel value exceeds a preset decibel value, when thetemperature variation of the M temperatures matches a normal temperaturerising trend; wherein if a determining result is positive, a cryingalarm or a coughing alarm is transmitted.
 13. The visible-light-imagephysiological monitoring system as claimed in claim 1, wherein thedeep-learning module is built in the processing unit.
 14. Thevisible-light-image physiological monitoring system as claimed in claim1, further comprising: a second communication module mounted in thecasing and electrically connected to the processing unit; and a cloudserver linking to the processing unit through a second communicationmodule and the deep-learning module is built in the cloud server toidentify the at least one feature of the visible-light image anddetermine the coordinate of each of the at least one feature; whereinthe cloud server sends the processing unit the at least one feature ofthe visible-light image and the coordinate of each of the at least onefeature.